ACL RD-TEC 1.0 Summarization of W06-3808
Paper Title:
SEEING STARS WHEN THERE ARENT MANY STARS: GRAPH-BASED SEMI-SUPERVISED LEARNING FOR SENTIMENT CATEGORIZATION
SEEING STARS WHEN THERE ARENT MANY STARS: GRAPH-BASED SEMI-SUPERVISED LEARNING FOR SENTIMENT CATEGORIZATION
Authors: Andrew Goldberg and Xiaojin Zhu
Primarily assigned technology terms:
- algorithm
- bayes classifier
- binary classifier
- categorization
- classification
- classifier
- classifiers
- computational linguistics
- cross validation
- feature representation
- inductive learning
- learner
- learning
- learning algorithm
- learning algorithms
- learning framework
- learning method
- learning process
- learning techniques
- loss function
- machine learning
- machine learning algorithms
- machine learning techniques
- multi-class classification
- mutual-information
- optimization
- parsing
- rating
- rating system
- regression
- semi-supervised learning
- sentiment analysis
- supervised learning
- supervised machine learning
- support vector regression
- svm classifier
- svm regression
- text categorization
- transduction
- tuning
- validation
- vector regression
Other assigned terms:
- 10-fold cross validation
- approach
- association for computational linguistics
- author corpora
- bias
- case
- corpora
- cosine similarity
- data set
- document
- edge weight
- fact
- feature
- hard constraint
- implementation
- knowledge
- labeling
- linguistic
- linguistic knowledge
- linguistics
- mapping
- measure
- measures
- method
- mutual information
- opinion
- optimization problem
- process
- rating-inference problem
- representations
- sentences
- sentiment
- set size
- similarity measure
- similarity measures
- statistical significance
- support vector
- terms
- test set
- text
- text documents
- topics
- training
- training data
- unlabeled examples
- web site
- word
- word vector
- word vector similarity
- words
